Automatic groove identification in 3D bullet land scans

Background: Bullet Lands

• When a gun is fired, the bullet is propelled forward through the barrel.
  
• As the bullet travels down the barrel, it makes contact with parts of the barrel.
  
• This is how we get striations!
  
• We get two different types of areas on the bullet: the lands and the grooves.

Background: Collection of Land Data

• Sensofar 3D Scanning Microscope
  
• A scan of one bullet (6 individual lands) takes ~1 hour

Importance of Groove Removal

• Bullet matching algorithm
  
• Removing the underlying curved structure of land
• Looking at remaining residuals
  • Deviations from the natural curve of the land

Shortcomings of Current Methods

Robust Linear Models

Groove Identification Process

• Once we have the residuals, how do we decide where the cutoffs should be?
  

Results

• We will look at all the residuals in the areas between our predicted grooves and the manually identified grooves
  
• To assess each method, we can take the mean of these residuals for each method over the whole dataset
  
• 208 total lands

##           Left Groove Right Groove
## Rollapply    223.1890     589.0630
## Quadratic    239.6362     229.6140

Acknowledgments

• All work was sponsored by CSAFE (Center for Statistics and Applications in Forensic Evidence), a NIST Center of Excellence